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Objectives - Build velocity model: Develop a data driven approach for velocity prediction. Assess saturation models: Use ML to develop a data and a physical model-driven approach to estimate CO2 saturation (SCO2).
SUMMARY Full-wavefield elastic imaging of active-source seismic data acquired by downhole receivers commonly offers higher-resolution subsurface images in the vicinity of a borehole compared to conventional surface seismic data sets, which can lack higher-frequency wavefield components due to longer travel paths and increased attenuation. An increasingly used approach for downhole acquisition is vertical seismic profiling (VSP), which has become more attractive when coupled with distributed acoustic sensing (DAS) using optical fibres installed in wells. The main difficulty for generating high-quality images with full-wavefield imaging tools for DAS VSP data, though, is the need for an accurate velocity model. To build plausible velocity models using active-source DAS VSP data, we adopt a 3-D image-domain elastic transmission tomography technique, originally developed for surface-recorded passive (microseismic) data, by exchanging the source and receiver positions (i.e. reciprocity) to mimic a passive-seismic surface monitoring scenario. The inversion approach exploits various images for each source constructed through time-reverse imaging (TRI) of downgoing P- and S-wave first-arrival waveforms. The TRI process uses the kinetic term of the (extended) PS energy imaging condition that exhibits sufficient sensitivity to velocity model errors. The method automatically updates the P- and S-wave velocity models to optimize image focusing via adjoint-state inversion. We illustrate the efficacy of the adopted elastic inversion technique using an active-source DAS 3-D VSP field data set acquired in the North Slope of Alaska. The numerical experiments demonstrate that the inverted elastic velocity models can be further used in full-wavefield acoustic/elastic imaging algorithms to obtain accurate subsurface images.
Seismic attenuation poses challenges to velocity model building from acoustic/elastic full-waveform inversion (FWI). In particular, when constructing the FWI gradient for velocity inversion, recent studies have indicated that the high-attenuation structure could distort the gradient by damping the amplitudes and shifting the kinematic phases, resulting in an imbalanced update and thus unreliable velocity model. These Q effects are particularly significant in the reflection acquisition geometry due to the “double-damping” issue. Here, we develop a Q-compensated FWI algorithm for constructing a Q-free FWI gradient. By using a recently developed viscoacoustic wave propagator, this compensation can be done conveniently by keeping the dispersion term and flipping the dissipation term in the wave equation when we simulate the forward and time-reversed adjoint wavefields. The resultant gradient obtained by interacting these two wavefields has correct kinematics and Q-free amplitudes. This Q-compensated FWI can balance the update between Q- and no- Q-areas, which we determine using synthetic examples. In addition, we illustrate how to take advantage of the dissipation-dispersion decoupling to determine the anomalous Q value in the Q model building workflow via Q-compensated reverse time migration.
To effectively overcome the cycle-skipping issue in full waveform inversion (FWI), we developed a deep neural network (DNN) approach to predict the absent low-frequency components by exploiting the hidden physical relation connecting the low- and the high-frequency data. To efficiently solve this challenging nonlinear regression problem, two novel strategies were proposed to design the DNN architecture and to optimize the learning process: (1) dual data feed structure; (2) progressive transfer learning. With the dual data feed structure, not only the high-frequency data, but also the corresponding beat tone data are fed into the DNN to relieve the burden of feature extraction. The second strategy, progressive transfer learning, enables us to train the DNN using a single evolving training dataset. Within the framework of the progressive transfer learning, the training dataset continuously evolves in an iterative manner by gradually retrieving the subsurface information through the physics-based inversion module, progressively enhancing the prediction accuracy of the DNN and propelling the inversion process out of the local minima. Here, the synthetic numerical experiments suggest that, without any a priori geological information, the low-frequency data predicted by the progressive transfer learning are sufficiently accurate for an FWI engine to produce reliable subsurface velocity models free of cycle-skipping artifacts.
Detailed simulations of the Atmospheric boundary layer (ABL) provides information on wind velocity, direction and turbulence for optimizing the design of wind turbines and wind farms and their operations. Distributed wind turbines have been considered for use in urban or suburban areas for covering energy needs using a sustainable energy solution. Simulations of high Reynolds number turbulent ABL flows past obstacles can be used for the prediction of the velocity deficit and turbulence characteristics in the leeward side of building-like obstacles, allowing for the estimation of power losses and fatigue loads in wind turbines. However, fully three-dimensional simulations of high Reynolds number ABL flows using Large Eddy Simulation (LES) or Reynolds Average Navier-Stokes Simulations (RANS) continue to require large computational/ execution times. As a result, these 3D simulations may not be ideal tools for the rapid assessment of wind energy potential. In the present study, 3D numerical results from wall resolved RANS simulations were used for the development of a low order model that allows the rapid assessment of wind velocity and turbulence in the leeward side of an isolated building.
Previously measured mean velocity and turbulence intensity profiles in the wake of a 26.8-m long building 3.2 m high and transverse to the wind direction in an atmospheric boundary layer several hundred meters thick were compared with profiles at corresponding stations downstream of a 1/50-scale model on the floor of a large meteorological wind tunnel in a boundary layer 0.61 m in thickness. The validity of using model wake data to predict full scale data was determined. Preliminary results are presented which indicate that disparities result from differences in relative depth of logarithmic layers, surface roughness, and the proximity of upstream obstacles.
Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.
Experiments were carried out in a small wind tunnel in which atmospheric flow around buildings was simulated. Arrays of one, two, three, and four model buildings were tested, and wake profiles of velocity and turbulence were measured. The data indicate the effect of the buildings on the wind environment encountered by aircraft during landing or takeoff operations. It was possible to use the results to locate the boundaries of the air regions affected by the obstacles and to recommend preferred arrangements of buildings to maximize light safety.
Experiments were carried out in a small wind tunnel in which atmospheric flow around buildings was simulated. Arrays of one, two, three, and four model buildings were tested, and wake profiles of velocity and turbulence were measured. The data indicate the effect of the buildings on the wind environment encountered by aircraft during landing or takeoff operations. It was possible to use the results to locate the boundaries of the air regions affected by the obstacles and to recommend preferred arrangement of buildings to maximize light safety. Previously announced in STAR as N83-14430
The present study builds on prior work by taking advantage of the novel framework proposed by Griffin et al. (hereafter referred to as the GFM) as a baseline. The model is progressively extended to multicomponent reacting mixtures, accounting for differential diffusion and finite-rate chemistry in a similar fashion to Di Renzo & Urzay and Di Renzo et al. The accuracy of the present approach, as well the prior model of Di Renzo & Urzay, is assessed in an a priori sense for the first time in a turbulent reacting boundary layer, using the boundary-layer data of Williams et al. Five species are included in the present analysis, i.e., N s = 5, namely N 2 , O 2 , NO, N and O, a neutral mixture most representative of dissociation/recombination phenomena for temperatures below 6000 K. A schematic of a flow over a wedge representative of the described configuration is presented in Figure 1. The brief is organized as follows: In Section 2, the wall-model equations and the computational framework are presented. In Section 3, the a priori results of the proposed model are described and compared to the extended EWM. Finally, in Section 4, some conclusions are offered.
This paper presents two Computational Fluid Dynamics (CFD) models of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT). The TDT is a continuous-flow, closed circuit wind tunnel with a 16- by 16-foot slotted test section with cropped corners. The tunnel was originally built as the 19-ft Pressure Tunnel in 1938, but it was converted to the current transonic tunnel in the 1950s, with capabilities to use either air or heavy gas as the test medium. The first computational model describes the generation of an atmospheric-boundary-layer (ABL) profile inside the tunnel. An ABL, which includes both a wind profile and turbulence content, is one of the aerodynamic characteristics affecting the occurrence of wind-induced oscillations for a launch vehicle sitting on a pad. The challenging part of this analysis was modeling the turbulent flow inside the tunnel. This is due to the special ABL-generating hardware that was installed at the entrance of the TDT test section in order to change the downstream velocity profile and to introduce velocity fluctuations into the flow. The second CFD model builds on the computational aeroelastic results that were generated in support of the second Aeroelastic Prediction Workshop (AePW) for the NASA Benchmark Supercritical Wing (BSCW) configuration. During the AePW, the wing-only configuration (classical free-air model) was analyzed. In the current study, the flutter computations were conducted on the configuration as it was mounted in the TDT during the experiment. This includes the wing attached to the splitter plate that was attached to the wind-tunnel walls. The preliminary results show that the wind-tunnel walls marginally affect flutter prediction.
Velocity and turbulence profiles previously measured in the wake of a long building 3.2 m high, located in the field, transverse to the wind and in an atmospheric boundary layer several hundred meters thick are compared with wake profiles at corresponding longitudinal stations for a scale model of the building located in a large meteorological wind tunnel having a boundary layer thickness of 0.61 m to assess the accuracy of full scale wake profile predictions based on model tests. Results are presented which show that disparities in nondimensional profiles result from differences in relative depth of logarithmic layers and in surface conditions.
This paper presents a graph-based dynamic yaw model to predict the dynamic response of the hub-height velocities and the power of a wind farm to a change in yaw. The model builds on previous work where the turbines define the nodes of the graph and the edges represent the interactions between turbines. Advances associated with the dynamic yaw model include a novel analytical description of the deformation of wind turbine wakes under yaw to represent the velocity deficits and a more accurate representation of the interturbine travel time of wakes. The accuracy of the model is improved by coupling it with time- and space-dependent estimates of the wind farm inflow based on real-time data from the wind farm. The model is validated both statically and dynamically using large-eddy simulations. An application of the model is presented that incorporates the model into an optimal control loop to control the farm power output.
Wear-related failures of spherical roller bearings in the main bearing position of three-point mount wind turbines have been higher than expected and can contribute to higher than anticipated operation-and-maintenance costs. In this paper, the operational conditions of such a main bearing—including measured axial displacement and velocity subject to the estimated axial loads—are described for an instrumented, commercial wind turbine. The field measurements suggest a maximum axial speed between the bearing rings that is less than 2 millimeters per second. It is estimated that the axial speed between the ring and rollers is approximately 25% of this value. When compared to a speed of rolling from approximately 200–352 millimeters per second, the measured axial sliding is therefore significantly less than 1% of the speed of rolling. Previous numerical studies of lubricant film formation in rolling contacts have shown that the effect of axial sliding starts to be noticeable only when this ratio exceeds 10%; therefore, the axial velocity represents only a small disturbance to the nominal pure rolling case, and the influence on oil film building can be neglected. A simple analytic model of the main bearing motion was also developed and demonstrated similar displacement and velocity characteristics.
Wear related failures of spherical roller bearings in the main bearing position of three-point mount wind turbines have been higher than expected and can contribute to higher than anticipated operation-and-maintenance costs. In this paper, the operational conditions of such a main bearing, including measured axial displacement and velocity subject to the estimated axial loads are described for an instrumented, commercial wind turbine. The field measurements suggest a maximum axial speed between the bearing rings that is less than 2 millimeters per second. It is estimated that the axial speed between the ring and rollers is approximately 25% of this value. When compared to a speed of rolling from approximately 200-352 millimeters per second, the measured axial sliding is therefore significantly less than 1% of the speed of rolling. Previous numerical studies of lubricant film formation in rolling contacts have shown that the effect of axial sliding starts to be noticeable only when this ratio exceeds 10%; therefore, the axial velocity represents only a small disturbance to the nominal pure rolling case, and the influence on oil film building can be neglected. A simple analytic model of the main bearing motion was also developed and demonstrated similar displacement and velocity characteristics.
It is now generally accepted that solid bodies in the solar system are formed by accumulation of solid grains. The mechanism of formation of smaller bodies, less than some tens of kilometers in radius, is investigated. These include planetesimals and comets. Results indicate that essentially complete agglomeration occurs for relative velocities of less than about 1000 cm/sec and fairly efficient mass build-up occurs up to 5000/cm. These velocities are consistent with current models of the primordial solar nebula. The temperature produced in a collision will be under 20 K. For ice/dust grains, the resultant aggregates will be of low density with their volatiles preserved. Cometary nuclei with radii of a few km will be irregularly shaped and fragile with low mean density and significant interanl density variations. The characteristics of such a structure could account for the observed properties of comets.
The goal of the NASA ACC High Energy Dynamic Impact Project is to determine the state of the art of dynamic fracture simulations for high velocity impact for composite fuselage shielding applications. Using a building block approach, several computational models considered under NASA ACC are being validated against test data, starting at unconfigured panels and progressing to configured panels under combined out-of-plane and in-plane loading due to ballistic impact. The computational models being evaluated in this project include MAT 162, MAT 213, MAT 261, SPG, and Peridynamics. In this paper, the simulation results using LS-Dyna Material MAT 261 are presented. In particular, a series of blind predictions for unconfigured panels were performed to determine the ballistic limit or V50 velocity. MAT 261 employs failure approach that is generally physically-based using fracture toughness criteria. The overall material model relies on typical ply-level stiffness properties, similar to MAT 162 and other composite continuum damage material models. The fracture toughness values are based on standard tests, and thus are not subject to extensive calibration. This approach is more efficient than performing extensive optimization studies for calibration of parameters. Also, this approach of relying on physical properties reduces the uncertainty of results, as questions concerning the quality and extent of the calibration studies is no longer relevant. However, it was found that carefully controlled coupon-level tests are needed to accurately obtain the required fracture toughness values. Additionally, it should be noted that there is one significant parameter in MAT 261 that does appear to require calibration, and that is the overall failure strain. This is the strain at which the element is deleted, and is not the same as the strain at which damage begins to accumulate. This failure strain is termed EFS (Effective Failure Strain), and is the maximum effective stain for element failure. Simulations have shown that this value will significantly affect impact response and failure. The paper presents the effect of this element failure strain parameter, along with possible uncertainties in fracture toughness values. With an adjusted appropriate value for EFS, it is seen that simulation results compare well with impact test data for predicted penetration velocity.
Measurements of longitudinal mean velocity and turbulence intensity were made in the wake of a rectangular model building in a simulated atmospheric boundary-layer wind. The model building was a 1:50 scale model of a structure used in a wake measurement program at the George C. Marshall Space Flight Center 8-tower boundary-layer facility. The approach wind profile and measurement locations were chosen to match the field site conditions. The wakes of the building in winds from azimuths of 0 and 47 degrees referenced to the normal to the building long axis were examined. The effect of two lines of trees upwind of the building on the wake and the importance of the ratio of the building height to boundary-layer thickness on the extent of the wake were determined.